Optimizing UAV Hyperspectral Imaging for Urban Tree Chlorophyll and Leaf Area Index Retrieval
Uncrewed aerial vehicle (UAV) based hyperspectral imaging offers a flexible method for monitoring urban trees. However, its effect on estimating biochemical and biophysical parameters is still unknown. This article examines how spatial and spectral resolution, solar zenith angle (SZA), and diffuse s...
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IEEE
2025-01-01
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| Series: | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
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| Online Access: | https://ieeexplore.ieee.org/document/10759629/ |
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| author | Shanshan Wei Tiangang Yin Bo Yuan Kim Hwa Lim Soo Chin Liew Andrew J. Whittle |
| author_facet | Shanshan Wei Tiangang Yin Bo Yuan Kim Hwa Lim Soo Chin Liew Andrew J. Whittle |
| author_sort | Shanshan Wei |
| collection | DOAJ |
| description | Uncrewed aerial vehicle (UAV) based hyperspectral imaging offers a flexible method for monitoring urban trees. However, its effect on estimating biochemical and biophysical parameters is still unknown. This article examines how spatial and spectral resolution, solar zenith angle (SZA), and diffuse solar irradiance (SKYL) affect chlorophyll content (C<sub>ab</sub>) and leaf area index (LAI) estimation using narrow-band indices (NBIs) through three-dimensional radiative simulations. The results show that spatial resolution minimally affects C<sub>ab</sub> estimation but significantly impacts LAI, with finer resolutions improving correlation with NBIs. In contrast, spectral resolution has little effect on LAI but greatly influences C<sub>ab</sub>, with a 2-nm resolution providing stronger correlations, while resolutions coarser than 6 nm are less sensitive. The C<sub>ab</sub> estimation prefers oblique SZAs, while LAI favors nadir SZAs. SKYL has little effect on C<sub>ab</sub> and minor impact on LAI. Sunlit pixels outperform shaded ones for C<sub>ab</sub> estimation, even at 2-m resolution, while entire-crown pixels show the highest LAI correlation. Different NBI strategies significantly affect LAI estimation but not C<sub>ab</sub>. A consistent conclusion emerges from the analysis of correlations between UAV hyperspectral imagery, with varying spatial and spectral resolutions, and corresponding C<sub>ab</sub> field measurements. This suggests that the knowledge revealed by the radiative transfer model is applicable to real-world conditions and improves understanding of natural processes without direct measurements.This article enhances the understanding of the influence of observation configurations on C<sub>ab</sub> and LAI estimation, offering insights to optimize UAV-based hyperspectral imaging and guide future satellite sensor development for tree monitoring. |
| format | Article |
| id | doaj-art-9776f6dd108f4cb6b61242f2f602b767 |
| institution | DOAJ |
| issn | 1939-1404 2151-1535 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
| spelling | doaj-art-9776f6dd108f4cb6b61242f2f602b7672025-08-20T02:48:45ZengIEEEIEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing1939-14042151-15352025-01-011883985210.1109/JSTARS.2024.349890010759629Optimizing UAV Hyperspectral Imaging for Urban Tree Chlorophyll and Leaf Area Index RetrievalShanshan Wei0https://orcid.org/0000-0002-2831-3864Tiangang Yin1https://orcid.org/0000-0002-2149-6004Bo Yuan2Kim Hwa Lim3https://orcid.org/0000-0002-8868-7868Soo Chin Liew4https://orcid.org/0000-0001-8342-4682Andrew J. Whittle5https://orcid.org/0000-0001-5358-4140Centre for Remote Imaging, Sensing and Processing, National University of Singapore, SingaporeDepartment of Land Surveying and Geo-Informatics, The Hong Kong Polytechnic University, Hong KongSchool of Information Engineering, Zhejiang Ocean University, Zhoushan, ChinaCentre for Remote Imaging, Sensing and Processing, National University of Singapore, SingaporeCentre for Remote Imaging, Sensing and Processing, National University of Singapore, SingaporeDepartment of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, MA, USAUncrewed aerial vehicle (UAV) based hyperspectral imaging offers a flexible method for monitoring urban trees. However, its effect on estimating biochemical and biophysical parameters is still unknown. This article examines how spatial and spectral resolution, solar zenith angle (SZA), and diffuse solar irradiance (SKYL) affect chlorophyll content (C<sub>ab</sub>) and leaf area index (LAI) estimation using narrow-band indices (NBIs) through three-dimensional radiative simulations. The results show that spatial resolution minimally affects C<sub>ab</sub> estimation but significantly impacts LAI, with finer resolutions improving correlation with NBIs. In contrast, spectral resolution has little effect on LAI but greatly influences C<sub>ab</sub>, with a 2-nm resolution providing stronger correlations, while resolutions coarser than 6 nm are less sensitive. The C<sub>ab</sub> estimation prefers oblique SZAs, while LAI favors nadir SZAs. SKYL has little effect on C<sub>ab</sub> and minor impact on LAI. Sunlit pixels outperform shaded ones for C<sub>ab</sub> estimation, even at 2-m resolution, while entire-crown pixels show the highest LAI correlation. Different NBI strategies significantly affect LAI estimation but not C<sub>ab</sub>. A consistent conclusion emerges from the analysis of correlations between UAV hyperspectral imagery, with varying spatial and spectral resolutions, and corresponding C<sub>ab</sub> field measurements. This suggests that the knowledge revealed by the radiative transfer model is applicable to real-world conditions and improves understanding of natural processes without direct measurements.This article enhances the understanding of the influence of observation configurations on C<sub>ab</sub> and LAI estimation, offering insights to optimize UAV-based hyperspectral imaging and guide future satellite sensor development for tree monitoring.https://ieeexplore.ieee.org/document/10759629/Chlorophyll content (C<named-content xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:ali="http://www.niso.org/schemas/ali/1.0/" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" content-type="math" xlink:type="simple"> <inline-formula> <tex-math notation="LaTeX">$_ab$</tex-math> </inline-formula> </named-content>)hyperspectral remote sensingleaf area index (LAI)uncrewed aerial vehicles (UAVs) |
| spellingShingle | Shanshan Wei Tiangang Yin Bo Yuan Kim Hwa Lim Soo Chin Liew Andrew J. Whittle Optimizing UAV Hyperspectral Imaging for Urban Tree Chlorophyll and Leaf Area Index Retrieval IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing Chlorophyll content (C<named-content xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:ali="http://www.niso.org/schemas/ali/1.0/" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" content-type="math" xlink:type="simple"> <inline-formula> <tex-math notation="LaTeX">$_ab$</tex-math> </inline-formula> </named-content>) hyperspectral remote sensing leaf area index (LAI) uncrewed aerial vehicles (UAVs) |
| title | Optimizing UAV Hyperspectral Imaging for Urban Tree Chlorophyll and Leaf Area Index Retrieval |
| title_full | Optimizing UAV Hyperspectral Imaging for Urban Tree Chlorophyll and Leaf Area Index Retrieval |
| title_fullStr | Optimizing UAV Hyperspectral Imaging for Urban Tree Chlorophyll and Leaf Area Index Retrieval |
| title_full_unstemmed | Optimizing UAV Hyperspectral Imaging for Urban Tree Chlorophyll and Leaf Area Index Retrieval |
| title_short | Optimizing UAV Hyperspectral Imaging for Urban Tree Chlorophyll and Leaf Area Index Retrieval |
| title_sort | optimizing uav hyperspectral imaging for urban tree chlorophyll and leaf area index retrieval |
| topic | Chlorophyll content (C<named-content xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:ali="http://www.niso.org/schemas/ali/1.0/" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" content-type="math" xlink:type="simple"> <inline-formula> <tex-math notation="LaTeX">$_ab$</tex-math> </inline-formula> </named-content>) hyperspectral remote sensing leaf area index (LAI) uncrewed aerial vehicles (UAVs) |
| url | https://ieeexplore.ieee.org/document/10759629/ |
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